Results 201 to 210 of about 23,267 (265)

Information behavior patterns and subjective digital well‐being: An exploratory study on perceptions of adults living in Germany

Journal of the Association for Information Science and Technology, Volume 77, Issue 5, Page 727-746, May 2026.
Abstract This exploratory study examines patterns of digital information behaviors such as information seeking, use, sharing, evaluation, avoidance, and curation to determine how they relate to subjective digital well‐being. To explore adults' personal views on their digital well‐being, conceptualized here as subjective digital well‐being, this study ...
Leyla Dewitz
wiley   +1 more source

Accelerated‐USE: A Benchmark Framework for GPU‐Driven Graph Neural Network Training

Concurrency and Computation: Practice and Experience, Volume 38, Issue 9, May 2026.
ABSTRACT Graph processing is used in many domains to extract knowledge from real‐world data. With the rise of deep neural networks and scaled compute infrastructure in artificial intelligence (AI), specialized techniques emerged to leverage graphs in applications such as recommendation systems and social networks.
Lucas de Angelo Martins Ribeiro, Willian Borges de Lemos, Vanessa Telles da Silva, Marcelo de Gomensoro Malheiros, Nelson Lopes Duarte Filho, Marcelo Rita Pias   +5 more
wiley   +1 more source

Conversing with machines: How AI is changing the way scientists think

Quantitative Biology, Volume 14, Issue 2, June 2026.
Anna Viktorovna Gavrilova, Carlo Galli
wiley   +1 more source

Optimization and Benchmarking of Lightweight Neural Networks for Efficient Embedded AI Deployment

Engineering Reports, Volume 8, Issue 5, May 2026.
A hardware‐aware optimization and benchmarking framework for lightweight neural networks is presented for deployment on heterogeneous embedded platforms including CPU, GPU, TPU, and MCU architectures. Model compression techniques such as quantization, pruning, knowledge distillation, and mixed‐precision computation reduce inference latency, memory ...
Vidapankal Mohammad Fridous, Abhishek Agarwal, K. B. Bhaskar, V. Nandagopal, N. Sivakamasundari   +4 more
wiley   +1 more source

DRLO-VANET: a deep reinforcement learning-based offloading framework for low-latency and energy-efficient task execution in VANETs. [PDF]

Sci Rep
Neelima S, Sree SR, Ramakrishnaiah N.
europepmc   +1 more source

Can Artificial Intelligence Foster Deep Personalization in Education?

Future Humanities, Volume 4, Issue 1, May 2026.
ABSTRACT Proposals for the adoption of artificial intelligence (AI) in education are often accompanied by claims that it promotes ‘personalization’. However, the concept of personalization has been narrowly and ambiguously framed. This paper traces the genealogy of the notion of personalization in education, highlighting its roots in Anglo‐Saxon ...
Santiago Tomás Bellomo, Karen Sun
wiley   +1 more source

Joint optimization of system utility in UAV-enabled edge computing. [PDF]

PLoS One
Zuo H, Zhang E, Tang Y, Yin M, Dong W.
europepmc   +1 more source

Performance Evaluation of Privacy Models for Data Streams on the Edge

Internet Technology Letters, Volume 9, Issue 3, May/June 2026.
ABSTRACT Recent advances in edge computing enable data stream privacy enforcement directly on resource‐constrained devices, reducing latency and the exposure of sensitive information. In this paper, we extend and validate our previously proposed privacy‐enforcing framework, which allows high‐level privacy policies to be expressed as chains of triggers ...
Ilir Murturi, Boris Sedlak, Reza Farahani, Schahram Dustdar   +3 more
wiley   +1 more source

A bi-level mobility-aware deep reinforcement learning approach for fault-tolerant task offloading in vehicular edge-cloud computing. [PDF]

Sci Rep
Babaiyan V, Bushehrian O, Javidan R.
europepmc   +1 more source